SOTAVerified

Emotional Intelligence

Emotional Intelligence (EI) is a measure of "The ability to monitor one’s own and others’ feelings, to discriminate among them, and to use this information to guide one’s thinking and action." (Salovey and Mayer, 1990). EI is further broken down into four branches: perceiving, using, understanding and managing emotions (Mayer & Salovey, 1997). Of particular relevance to language models that operate exclusively in the text modality is emotional understanding (EU). This is defined as the ability to interpret and analyse the language of emotions, to comprehend complex emotional states, and understand how these emotions can influence behaviour and decision-making.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 77 papers

TitleStatusHype
Emotional Intelligence of Large Language Models—0
Large Language Models Understand and Can be Enhanced by Emotional Stimuli—0
Empirical Interpretation of the Relationship Between Speech Acoustic Context and Emotion Recognition—0
Synthesizing Affective Neurophysiological Signals Using Generative Models: A Review Paper—0
Reevaluating Data Partitioning for Emotion Detection in EmoWOZ—0
Machine Learning Algorithms for Depression Detection and Their Comparison—0
Emotion Twenty Questions Dialog System for Lexical Emotional IntelligenceCode0
The Nexus between Job Burnout and Emotional Intelligence on Turnover Intention in Oil and Gas Companies in the UAE—0
The SPACE THEA Project—0
HICEM: A High-Coverage Emotion Model for Artificial Emotional Intelligence—0
Continuing Pre-trained Model with Multiple Training Strategies for Emotional Classification—0
Multimodal Emotion Recognition using Transfer Learning from Speaker Recognition and BERT-based models—0
Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence—0
occ2vec: A principal approach to representing occupations using natural language processing—0
Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies—0
Affective Image Content Analysis: Two Decades Review and New Perspectives—0
Lie-Sensor: A Live Emotion Verifier or a Licensor for Chat Applications using Emotional Intelligence—0
Investigating Emotion-Color Association in Deep Neural NetworksCode0
Empirical Interpretation of Speech Emotion Perception with Attention Based Model for Speech Emotion Recognition—0
Future Trends for Human-AI Collaboration: A Comprehensive Taxonomy of AI/AGI Using Multiple Intelligences and Learning Styles—0
Controllability Analysis of Functional Brain Networks—0
Learning Transferable Features for Speech Emotion Recognition—0
Deep Multi-Facial patches Aggregation Network for Expression Classification from Face Images—0
Investigating Audio, Video, and Text Fusion Methods for End-to-End Automatic Personality Prediction—0
Investigating Audio, Visual, and Text Fusion Methods for End-to-End Automatic Personality Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OpenAI gpt-4-0613EQ-Bench Score62.52—Unverified
2migtissera/SynthIA-70B-v1.5EQ-Bench Score54.83—Unverified
3OpenAI gpt-4-0314EQ-Bench Score53.39—Unverified
4Qwen/Qwen-72B-ChatEQ-Bench Score52.44—Unverified
5Anthropic Claude2EQ-Bench Score52.14—Unverified
6meta-llama/Llama-2-70b-chat-hfEQ-Bench Score51.56—Unverified
701-ai/Yi-34B-ChatEQ-Bench Score51.03—Unverified
8OpenAI gpt-3.5-0613EQ-Bench Score49.17—Unverified
9OpenAI gpt-3.5-turbo-0301EQ-Bench Score47.61—Unverified
10Open-Orca/Mistral-7B-OpenOrcaEQ-Bench Score44.4—Unverified